1. Field of the Invention
The present invention generally relates to the field of advanced process control of manufacturing processes, such as processes for producing semiconductor products, wherein an improved process control quality is achieved by adjusting process parameters on the basis of a process model and information related to, for example, the product, the type of process, the process tool to be used, and the like, to determine a process state describing the expected effect of the process on the product.
2. Description of the Related Art
Today's global market forces manufacturers of mass products to offer high quality products at a low price. It is thus important to improve yield and process efficiency to minimize production costs. This holds especially true in the field of semiconductor fabrication, since here it is essential to combine cutting-edge technology with mass production techniques. It is, therefore, the goal of semiconductor manufacturers to reduce the consumption of raw materials and consumables while at the same time improving process tool utilization. The latter aspect is especially important, since in modern semiconductor facilities, equipment is required which is extremely cost-intensive and represents the dominant part of the total product costs. For example, in manufacturing modern integrated circuits, 500 or more individual processes may be necessary to complete the integrated circuit, wherein failure in a single process step may result in the loss of the complete integrated circuit. This problem is even exacerbated in that the size of the substrate, on which a plurality of such integrated circuits are processed, steadily increases, so that failure in a single process step may entail the loss of a large number of products. Therefore, the various manufacturing stages have to be thoroughly monitored to avoid undue waste of tool operation time and raw materials. Ideally, the effect of each individual process step on each substrate would be detected by measurement and the substrate under consideration would be released for further processing only if the required specifications were met. A corresponding process control, however, is not practical, since measuring the effects of certain processes may require relatively long measurement times or may even necessitate the destruction of the sample. Moreover, immense effort, in terms of time and equipment, would have to be made on the metrology side to provide for the required measurement results. Additionally, utilization of the process tool would be minimized since the tool would be released only after the provision of the measurement result and its assessment.
The introduction of statistical methods, i.e., mean values, etc., for adjusting process parameters significantly relaxes the above problem and allows a moderate utilization of the process tools while attaining a relatively high product yield. Nevertheless, in total, a large number of dummy substrates or pilot substrates may be necessary to adjust process parameters of respective process tools, wherein tolerable parameter drifts during the process have to be taken into consideration when designing a process sequence. This criterion is often referred to as the process capability for the process under consideration.
Recently, a process control strategy has been introduced and is continuously improved, allowing a high degree of process control, desirably on a run-to-run basis, without the necessity of an immediate response of a measurement tool. In this control strategy, the so-called advanced process control, a model of a process or of a group of interrelated processes is established and implemented in an appropriately configured process controller. The process controller also receives information related to the type of process or processes, the product, the process tool or process tools in which the products are to be processed, the process recipe to be used, i.e., a set of required sub-steps for the process or processes under consideration, wherein possibly fixed process parameters and variable process parameters may be contained, measurement results of previously processed products or test substrates, and the like. From this information, which may also be referred to as history information, and the process model, the process controller determines a controller state or process state that describes the effect of the process or processes under consideration on the specific product.
With reference to FIGS. 1a-1b, an illustrative example of an advanced process control (APC) will now be described. FIG. 1a schematically shows an APC architecture that is exemplified for a chemical mechanical polishing (CMP) process. A CMP station 100 comprises three individual operable CMP platens 101, 102 and 103. A process controller 110 is operatively connected to the CMP station 100. Moreover, the process controller 110 is configured to receive information from a metrology tool 120 and from the CMP tool 100. Furthermore, the process controller 110 may receive information related to a product 130 to be processed by the CMP station 100, and information related to a process recipe 140 that generally specifies the type of process to be performed on the CMP station 100.
The operation of the system shown in FIG. 1a will be explained with reference to the flowchart shown in FIG. 1b. First, in step 150, the process controller 110 is initialized, i.e., the process controller 110 is set to an initial process state. A process state in this example may represent, for instance, the removal rate at each of the CMP platens 101, 102 and 103. The process state may also represent the removal rate and the associated degree of dishing and erosion at each of the CMP platens, or may represent the total removal rate of the CMP station 100. Since, generally, the amount of history information available upon initialization of the process controller 110 may not be sufficient to determine a process state, the initial state is set in advance and selected so that the effect of the tool is expected to be within the process specifications. The product 130 is then processed with process parameters adjusted on the basis of the initial process state.
In step 155, the process controller 110 determines a process state on the basis of the process model implemented and the history information received from, for example, the metrology tool 120, the CMP station 100, a further product 130 to be processed and the corresponding process recipe. It should be noted that, in particular, the measurement results obtained from the metrology tool 120 may be delayed or may not even be available unless a plurality of products 130 is completely processed. Thus, the process controller 110 establishes the currently valid process state on the basis of the available information and the process model to “predict” the effect of the CMP process on the product to be processed and to adjust process parameters correspondingly to achieve the predicted effect. For example, the process controller 110 may estimate the wear of the polishing pads on the platens 101, 102 and 103 from the available information, such as the number of products that has already been processed, type of process to be performed and the like, and estimate the “state” of the process and correspondingly adjust a process parameter, for example, the polishing time on a specific polishing platen, to obtain the specified process result. In other processes, the process state may represent the etch rate in an etch tool, the gate length in forming a gate electrode of a MOS transistor, the deposition rate in a deposition tool, and so on.
As indicated in step 160, the determination of the process state may require the processing of one or more pilot substrates so as to improve control quality, since the accuracy of the determined process state may significantly depend on the available history information, the amount and the exactness of which increases with an increasing number of processed products.
In step 165, the process state is updated, that is, a new or advanced process state is determined on the basis of the previous process states, including the previously obtained history information. Preferably, the advanced process state is established on a run-to-run basis; that is, prior to processing an individual product 130, the corresponding process state is established, and on the basis of the currently valid process state, the process parameter(s) may accordingly be adjusted.
As indicated in step 170, the process flow continuously updates the process state when no reset event occurs. Generally, process control quality improves as the amount of history information increases, unless the history information indicates that predefined specifications are no longer met. For instance, the lifetime of a consumable has expired or will soon expire, a polishing head has to be replaced, a machine failure has occurred, the type of product is to be changed, or the process recipe, i.e., the type of process, has to be changed, and the like. Any of these events may render the process state unpredictable and, therefore, the process controller 110 is re-initialized with the initial state set in advance and the process continues as depicted in FIG. 1b on the basis of newly gathered history information after the reset event.
It should be noted that the system shown and described with reference to FIGS. 1a-1b is only an illustrative example, wherein the process controller 110 is connected to a single process station and is used in a feedback loop; however, the process controller 110 may be configured so as to perform several control operations with a plurality of different product types and process recipes, as well as with more than one process tool. Furthermore, the process controller 110 may be adapted to perform a feed forward operation, i.e., control process on the basis of history information relating to a previously completed process to adjust parameters of a subsequent process.
Although the advanced process control, as exemplarily described above, provides significant advantages compared with process controls based, for example, on measurement mean values, the occurrence of reset events conventionally requires the re-initializing of the process controller, resulting in a reduced process quality in an early state after the re-initialization and also possibly requiring the processing of additional pilot substrates.
Any re-initialization, however, reduces the process capability due to a wider range of tolerances of the process during the time period after the re-initialization, and entails a reduced throughput due to the processing of pilot wafers and a reduced yield caused by a higher probability of device failures.
It is thus highly desirable to reduce the inadvertent effect of reset events on product yield and production cost.